Determination of Moisture Content and Basic Density of Poplar Wood Chips under Various Moisture Conditions by Near-Infrared Spectroscopy

Abstract

The potential of near-infrared (NIR) spectroscopy coupled with partial least-squares (PLS) regression was used to determine the moisture content and basic density of poplar wood chips. NIR spectra collected from the surface of wood chips were used to develop calibration models for moisture content and basic density predication, and various spectral preprocessing techniques were applied to improve the accuracy and robustness of the prediction models. The models were tested using totally independent sample sets and exhibited acceptable predictive performance for moisture content (coefficient of determination for prediction [R2p] = 0.98 and standard error of prediction [SEP] = 2.51 percent) and basic density (R2p = 0.87 and SEP = 17.61 kg m–3). In addition, the effect of moisture variations on prediction of basic density was investigated based on NIR spectra from wood chips under various moisture levels. The results demonstrated that broad absorption bands from water molecules, especially when free water exists in the cell lumen, overlap with informative signals related to wood properties and weaken the calibration relation between spectral features and basic density. Thus, maintaining wood chips in a low and even moisture state would help achieve reliable estimates of wood density by NIR analysis models.

Simultaneous detection of density, moisture content and fiber direction of wood by THz time-domain spectroscopy

“…Schajer and Orhan [19] successfully predicted the grain angles for hemlock and Douglas fir with standard errors of 0.9° and 2.5° (measured range from − 90 to + 90°), MC of 1.2 and 1.9% (measured range from 7 to 28%), and dry density of 0.16 and 0.30 g/cm 3 (measured range from 0.325 to 0.625 g/cm 3 ) [20]. Liang et al [20] exhibited an acceptable predictive performance by using NIR spectroscopy for the MC with a determination coefficient of 0.98 and a standard error of prediction of 2.51% and basic density with a determination [21]. In order to examine the source of error for the prediction of fiber direction and MC, we observed the prediction accuracy change with the MC of wood.…”

Analytical Methods for the Rapid Determination of Solid Biofuel Quality

“…Currently, several well‐investigated methods are available for the rapid determination of M in solid biofuels, such as capacitive measurement 60, 61, 230, TDR 60, 61, 126–128, electrical resistance 60, 61, 234, 236 infrared drying (gravimetric) 60, 256, NIRS 60, 86–96, 241, 242, microwave‐, or radio wave methods 60, 80, 120–125. Usually, most of these methods do not require any special sample preparation such as milling or grinding of the material and can be applied directly when fuels are delivered to the plant.…”

“…In particular, capacitive measurement, infrared drying and NIR spectroscopy have been investigated in detail in various studies in recent years 60, 61, 86–96, 241, 242. They usually show medium to good results in terms of instrument precision compared to the reference method (ISO 18134‐1 to ‐3) 13–15.…”

Anatomical, physical, and mechanical parameters of clone plantation tree, Cunninghamia lanceolata

“…The indirect methods include densitometric methods that are based on high-resolution imaging of differences in attenuation of non-visible radiation by the samples investigated (Diesel et al 2014). In addition to these traditional methods, near-infrared spectroscopy (NIRS) has the potential of predicting wood basic density rapidly and nondestructively (Liang et al 2019). In several tests, British Standards and ASTM (American Society for Testing and Materials) standard wood testing procedures are referred by researchers to analyze wood basic density (Sseremba et al 2020).…”